International price comparisons of Alzheimer's drugs: a way to close the affordability gap
Bibliographic record
Abstract
BACKGROUND: Alzheimer's drugs are believed to have limited availability and to be unaffordable in low- and middle-income countries compared to high-income countries. The price, availability and affordability of Alzheimer's drugs have not been reported before. METHODS: During 2007 an international survey was conducted in 21 countries in six continents (Argentina, Australia, Brazil, the Dominican Republic, France, India, Japan, Macedonia, Mexico, New Zealand, Nigeria, the Philippines, Portugal, Serbia, South Korea, Switzerland, Taiwan, Thailand, Uganda, the U.K. and the U.S.A.). Prices of Alzheimer's drugs were compared using the affordability index (the total number of units purchasable with one's daily income) derived from purchasing power parity (PPP) converted prices as well as raw prices. RESULTS: Donepezil is available in all 21 countries, whereas the newer drugs are less available. A 5 mg tablet of branded originator donepezil costs just US$0.26 in India and US$0.31 in Mexico, whereas it costs US$6.64 in the U.S.A. Pricing conditions of rivastigmine, galantamine and memantine appear to be similar to that of donepezil. The cheapest branded originators are from India and Mexico. However, in terms of PPP, Alzheimer's drugs in other low- and middle-income countries are much more expensive than in high-income countries. Most people in low- and middle-income countries cannot afford Alzheimer's drugs. CONCLUSIONS: Alzheimer's drugs, albeit available, are often unaffordable for those who need them most. It is hoped that equitable differential pricing will be applied to Alzheimer's drugs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".